There are many instances where it is necessary to detect recordings comprising occurrences of uttered keywords. Oftentimes, it is possible to identify recordings pertaining to a particular topic on the basis of the presence or absence of certain keywords in the recordings.
Audio quality in recorded telephone conversation is often less than ideal. Recorded call may be sampled at a low sampling rate, a low bit rate and may be compressed. In part for this reason, an effective automatic detection of certain types of calls has not been developed until now.
In many businesses where telephone interactions play a large role, telephone calls are recorded and stored such that they can be recalled at a later date if necessary. This is useful if the later need is to access a single, identified call record, however if it becomes necessary to identify or access call recordings on the bases of their conversation contents, an operator must listen to all the recorded calls and manually select the pertinent ones.
The need to identify from among a plurality of recording those containing certain keywords can arise in many contexts. For example, telephone transaction or phone calls related to transactions take place in the context of trading, such as in energy trading. In energy trading, like in other trading contexts, regulating authority may investigate certain matters and require industry players to produce their recordings related to certain transactions. This may involve producing telephone recordings pertaining to a certain topic. Currently, doing so requires the manual scanning of hours of recording by human operators. This can be an extremely wasteful use of resources and can result in very costly investigations, particularly when there are a lot of recordings to search from.
In the context of national security as well, there may be a need to scan hundreds and even thousands of hours of recording to identify calls pertaining to certain topic. Identification of calls pertaining to topics of interest may be done on the basis of the presence of keywords in the call. In the context of security in general, audio information of interest may be from sources other than telephone calls such as from the audio component of a security camera output or from security microphones.
In addition to searching through stored recordings, it is often necessary to search through live audio streams in real-time or near-real-time. For example in the context of corporate security, it may be desired to identify any telephone call in which confidential information is being discussed in real-time so that inadvertent or deliberate leaks may be prevented as they occur. Likewise in the context of national security, calls pertaining to very high-risk individuals or to present events may require an immediate security reaction.
In the context of the above, it can be appreciated that there is a need in the industry for a means of reducing the burden of identifying keywords occurrences in audio data.